Customized consumer loan product search system and method

ABSTRACT

A method and system for using Loan Level Pricing Adjustments corresponding to specific consumer input to determine or calculate the interest rates of a plurality of loan products, comprising searching from a plurality of available, relevant loan products with associated pricing, wherein the searching is based on input consumer criteria, and includes creating and updating a centralized and searchable database of lenders&#39; underwriting and pricing guidelines that can be utilized by a consumer; and matching and optimization of loan products or pricing for a consumer wherein the consumer&#39;s qualifications and needs are matched to the best available loan products with associated rate pricing and wherein the system comprises a single or plurality of wireless handheld devices each comprising an interactive interface through which are communicable customer attributes, and through which are returned results of determined or calculated customer eligibility.

CORRESPONDING RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.13/115,034, which in turn is a continuation of U.S. patent applicationSer. No. 11/390,805, the entire contents of which are incorporated byreference herein in its entirety.

FIELD OF INVENTION

The present invention relates generally to computer networks, and morespecifically, to a system and method to interface (web-based orotherwise) between consumers and lenders using software for databasemanagement and searching as well as matching of specific parameters.

BACKGROUND OF INVENTION

Computers have revolutionized the ways by which loans are provided tocustomers. With the advent of the Internet, there have been even moresubstantial technological advancements in the mortgage and financialservices industries. The Internet initially created an additionaldistribution channel for loan searching and origination generallythrough the use of application service providers. These entitiesdeveloped software to facilitate online interaction between a singularlender and an individual consumer, thereby creating another revolution.There are still a large number of 3^(rd) party software companies thatdo work on the back end for large banks and commercial lendinginstitutions to streamline their customers' back end operations andincrease overall efficiencies. In addition, most lenders now have theirown proprietary systems that can price a loan for a specific loanprofile but only for that lending institution's own set of proprietaryproducts. This limits the ability of a consumer to conveniently searchfor all loan products for which they may be qualified and to find theloan product with the best available rates.

Direct commercial lenders have come into existence whereby they offer alimited search and application process for consumers to wholesalelenders; however, the search methodology is poor and the search criteriais limited to the point that any loan search and pricing is generic andnot fully customized to a consumer's profiled requests and needs. Toimprove on this concept, online lead generators have attempted toalleviate a consumer's pain by receiving consumer information, filteringthat information toward pre-approved loans offered by lenders that areclosely associated with the online lead generator, and selling theconsumer information to brokers and/or lenders for future consumercontact. One of the many problems with this approach is that loanproduct rates are not a component of the limited search criteria, andthe consumer is unlikely to receive the best rate.

In addition to their traditional presence, loan brokers eventuallyreintroduced themselves to the online loan process as an intermediary bycreating broker software. This way, a loan broker could interact with afinite number of lenders, thereby providing the actual borrower withmore choices. The broker's software functions to provide mortgagebrokers and other professionals with limited information on lenders, thetypes of products they offer, and ideally the pricing of said products,but it does not function to inform the borrower especially as thatinformation relates to removing confusion regarding closing costs, fees,and yield spread which are all additional costs to the consumer.Unfortunately such broker software also prevents the borrower, the trueconsumer, from accessing critical information directly and introduces aninefficient if not unnecessary level of contact and adds cost to thelending, underwriting, and pricing process.

Finally, an online mortgage origination industry has also come intoexistence whereby loan products and pricing of multiple wholesalelenders are aggregated. Once applicable loan rates and pricing aredetermined for a consumer, that consumer's information can be passedalong to an online loan origination system to begin the actual loanapplication process. However, the consumer would not be certain of theirqualification for a loan product until they entered the loan applicationprocess. And furthermore, without a centralized and searchable databaseof the lenders' underwriting and pricing guidelines, the consumer cannot be certain that the loan product chosen for them is the best productfor their needs even if they did qualify.

To this day, the mortgage process remains fragmented and opaque whereina consumer is unable to know for certain if they can obtain or havereceived the loan that best meets their needs. The use of existingtechnology and a traditional loan broker does not solve the problemsbecause the broker also lacks the tools to confirm that he is gettingthe ‘best’ loan for the represented consumer. There is currently no waythat a consumer can match his qualifications and needs to the bestavailable loan products and determine the associated rate pricing,monthly payments, and fees of those products.

SUMMARY OF INVENTION

In light of the foregoing, a need in the art exists for methods thatcreate a centralized and searchable database of lenders' underwritingand interest rate pricing guidelines that can be utilized by theconsumer and for a system that matches the consumer's qualifications andneeds to the best available loan products with associated rate pricing.The consumer must directly search lenders to ensure that s/he obtainsthe loan that comes closest to matching the desired criteria and furtheravoids the broker process and associated fees. Embodiments of thepresent invention substantially fulfill this need.

In an embodiment of the present invention a computer automated methodfor creating, organizing, and updating a centralized and searchabledatabase of a plurality of lending institutions' underwriting andinterest rate pricing guidelines for loan products is utilized to searchfor the optimal loan products available. The method comprises the stepsof receiving a first lender subset database and receiving a secondlender subset database, modifying one or more subset databases with aminimum compliance level of data, and storing all subset databaseinformation in the loan broker lender database such that matching andoptimization of loan products or pricing for a consumer may beperformed. The first subset database and all subsequent lender subsetdatabases are comprised of at least a minimum compliance level of dataincluding the following lending institution underwriting and pricingguidelines: loan characteristics, qualifying ratios and limits, baserate pricing, yield spread rate pricing (also known as service releasepremium pricing, gain on sale pricing, or rebate pricing), and rateadd-ons.

The first lender subset database and one or more subsequent lendersubset databases are received and updated automatically or manually bycontacting a plurality of lending institutions via the Internet or othermeans of data transfer as further described below. Additionally, a firstlender subset database and one or more subsequent lender subsetdatabases could be received automatically by a plurality of lendinginstitutions updating a centralized web server via the Internet andcontributing a lending institution's subset database of underwriting andpricing guidelines to the loan broker lender database.

The first lender subset database and all subsequent lender subsetdatabases are organized into a numerical loan broker database matrixfunctioning as limits with the resulting data comprising the minimumcompliance level of data. Programming logic can then match the bestavailable loan products with associated rate pricing to the consumer'squalifications and needs found in the consumer profile described below.

A method of interfacing a customer computer or device to an additionalcomputer or device through a network interface for searching a loanbroker lender database comprising a plurality of lending institutions'underwriting and pricing guidelines on behalf of a customer is utilizedto search and qualify for, rank, and present the optimal loan productsavailable. The method comprises the steps of receiving and storingconsumer information within the additional computer or device,performing one or more calculations including use of the consumerinformation to obtain credit related values, and creating a consumerprofile comprising consumer information and the results of creditrelated value calculations.

The consumer information comprises loan and property informationincluding use of proceeds, property value, loan amount, down payment,cash-out amount, property location, property type, occupancy type,terms, length of loan, interest only loan or otherwise, length ofproperty ownership, total number of properties owned, acreage, or squarefootage. The consumer information also comprises income informationincluding type of income documentation, income, expenses, and value ofliquid assets, property taxes, insurance cost, or employmentinformation. The consumer information also comprises credit informationincluding credit score(s), credit self-ranking, tradelines, paymenthistory, bankruptcy history, consumer credit counseling history, orforeclosure or notice of default (NOD) history. The credit informationmay be received automatically by a centralized web server via theInternet.

Credit related value calculations performed by the additional computeror device comprise loan-to-value ratio (LTV), combined loan-to-valueratio (CLTV), front debt-to-income ratio (DTI), back DTI, disposableincome, total tradelines, principal, interest, property taxes, andinsurance (PITI) reserves, number of late payments, time sincebankruptcy, time since consumer credit counseling, or time sinceforeclosure or notice of default.

In an embodiment of the present invention a consumer is able to receivea ranking of available loan products presented according to interestrate, monthly payment, and/or Annual Percentage Rate (APR), or otheroutput in an interactive interface. A computer-accessible medium havingencoded thereon instructions to present a consumer with the availableloan products with associated pricing is utilized, wherein theinstructions, when executed by a computing apparatus, cause thecomputing apparatus to compare the consumer profile to existing lenderguideline criteria located in the loan broker lender database, rejectlenders that will not offer loan products to the consumer, compare theconsumer profile to available lender loan products, obtain a number ofavailable loan products, determine or calculate corresponding base rateor yield spread rate (also known as service release premium rate, gainon sale rate, or rebate rate) for the available loan products, and applyrate add-ons to determine or calculate lender rates for the loanproducts.

The instructions contained within the programming logic furtherautomatically determine or calculate a plurality of lendinginstitutions' criteria to combine and optimize product selectionaccording to the consumer profile to include multiple weighted productsfrom different lending institutions. The instructions furtherautomatically determine or calculate consumer output criteria comprisinglenders, loan products, rates, monthly payment totals, Annual PercentageRate (APR), or a portion of the consumer profile, and the instructionsfurther automatically determine or calculate consumer output criteriacomprising title insurance cost, or other closing costs and fees. Once aconsumer receives a ranking of available loan products presented from aleast expensive rate and monthly payment to a most expensive rate andmonthly payment or other output in an interactive interface, theinstructions further allow the consumer to modify their existingconsumer profile to obtain alternative lending institutions' productrankings based on alternative search criteria. Additionally, theinstructions further allow a consumer to initiate or complete atransaction for one or more of the loan products as presented in theconsumer output.

Other aspects and features of various embodiments disclosed herein willbecome apparent from consideration of the following description taken inconjunction with the accompanying drawings.

BRIEF DESCRIPTION OF DRAWINGS

Other objects and features of the present invention will become apparentfrom the following detailed description considered in connection withthe accompanying drawings which disclose several embodiments of thepresent invention. It should be understood, however, that the drawingsare designed for the purpose of illustration only and not as adefinition of the limits of the invention.

FIG. 1 shows a block diagram of a loan broker computing apparatusimplementing the present invention;

FIG. 2 shows a block diagram illustrating several components of thelender server of FIG. 1 used to obtain lender product data in accordancewith an embodiment of the present invention;

FIG. 3 shows a block diagram illustrating several components of thecustomer device of FIG. 1 used to obtain consumer data in accordancewith an embodiment of the present invention;

FIG. 4 shows a block diagram illustrating several components of thecredit bureau or alternative data server or device of FIG. 1 used toobtain credit rating or alternative data in accordance with anembodiment of the present invention;

FIG. 5 shows a block diagram illustrating several components of the loanbroker server of FIG. 1 used to obtain obtain/receive and store data,perform operations, and process and export data in accordance with anembodiment of the present invention;

FIG. 6 shows a representation of the loan broker lender database inaccordance with an embodiment of the present invention;

FIG. 7 shows an overview flow diagram illustrating information obtainedand logic implemented using the devices of FIG. 1 to create a customconsumer profile in accordance with an embodiment of the presentinvention;

FIG. 8 shows an overview flow diagram illustrating information obtainedand logic implemented using the devices of FIG. 1 to create a customloan broker lender database in accordance with an embodiment of thepresent invention;

FIG. 9 shows a programming logic flow diagram which illustrates theactions taken by the devices illustrated in FIG. 1 to match needs andqualifications of a consumer to the best available loan products andrates in accordance with an embodiment of the present invention;

FIGS. 10A-10D show representative examples of consumer output inaccordance with an embodiment of the present invention;

DETAILED DESCRIPTION OF EMBODIMENTS

The following terms have these corresponding definitions in thedescription:

AVAILABLE LOAN PRODUCT: A loan that a lender generally offers and willoffer to a potential consumer when the given attributes of that consumersatisfy the loan acceptance criteria.

BEST AVAILABLE LOAN PRODUCT: An available loan product or combination ofloan products selected by the programming logic and presented to thepotential consumer as possessing the best (i.e., most favorable ordesirable to the consumer based upon their custom consumer profile)attribute or combination of attributes relative to all other availableloan products.

CONSUMER PROFILE: Information about a consumer based on (1) inputprovided by the consumer or from alternative sources about the consumerand the loan type(s) they are seeking such as income and assetinformation, use of proceeds including, for example, value andadditional information about a property they may be buying orrefinancing, amount of loan, and credit information and (2) calculationsand programming performed by the loan broker server.

LENDER: A bank, finance company, mortgage bank, wholesale lender, orother entity in the business of providing loans.

LOAN ACCEPTANCE CRITERIA: Attributes the lender requires to be possessedby a potential consumer in order to make a loan available to thatconsumer.

MINIMUM COMPLIANCE LEVEL OF DATA: The baseline criteria required fordetermining loan eligibility and pricing that is uniformly collectedfrom each individual lender and is then modified as necessary,organized, and stored in conjunction with like criteria from all otherlending institutions. The aggregation of such criteria from each of theplurality of lending institution's underwriting and interest ratepricing guidelines forms the loan broker server's searchable andcentralized lender database for use in matching and optimizing loanproducts and associated interest rate pricing for a consumer. Thisbaseline criteria comprises: credit score, loan amount, cash-out amount,loan-to-value ratio (LTV), combined loan-to-value ratio (CLTV), frontDTI, back DTI, PITI reserve requirements, tradelines, payment history,bankruptcy history, foreclosure history/information, notice of defaulthistory/information, interest only versus fully amortizing, productterms, use of proceeds, lien position, property type, occupancy type,property location, documentation type, and employment type.

PLURALITY OF LENDERS: A group of lenders that are not affiliated in anyway other than in their participation in the loan market as competitorsfor loans.

QUALIFICATION ENGINE: The programming algorithms performed by the loanbroker server that determines if a consumer profile qualifies for one ormore of a plurality of lenders' loan products by comparison of theconsumer profile to the guidelines of the minimum compliance level ofdata.

Those skilled in the art will appreciate that the present invention maybe implemented with many different types of computer systemconfigurations, including hand-held devices, multiprocessor systems,microprocessor based or programmable consumer electronics, networkpersonal computers, minicomputers, mainframe computers, and the like.The present invention can also include multiple computer programs whichembody the functions described herein and illustrated in the drawings,flow charts, and programming logic. However, it should be apparent thatthere could be many different ways of implementing the invention incomputer programming, and the invention should not be construed aslimited to any one set of computer program instructions. Further, askilled programmer would be able to write such a computer program toimplement the disclosed invention without difficulty based on thedrawings, flow charts, and programming logic and associated descriptionin the application text, for example.

Therefore, disclosure of a particular set of program code instructionsis not considered necessary for an adequate understanding of how to makeand use the invention. The inventive functionality of the claimedcomputer program will be explained in more detail in the followingdescription in conjunction with the remaining Figures illustrating thefunctions and program flow. Certain steps in the program flow describedbelow must naturally precede others for the present invention tofunction as described. However, the present invention is not limited tothe order of the steps described if such order or sequence does notalter the functionality of the present invention. That is, it isrecognized that some steps may be performed before or after other stepsor in parallel with other steps without departing from the scope andspirit of the present invention.

FIG. 1 block diagram shows network system 40 having one or more loanbroker servers 50 and one or more client processors or nodes 10, 20, 30,coupled thereto. Those of ordinary skill in the art will appreciate thatthe network interface 130, 230, 330, 530 includes the necessarycircuitry for connecting the loan broker servers, client processors, ornodes to the network 40, and that the network interface 130, 230, 330,530 is also preferably constructed for use according to the standardTransmission Control Protocol/Internet Protocol (“TCP/IP”) protocol, theInternet Inter-ORB Protocol (“IIOP”), or other conventional digitalnetworking and data communications scheme.

Preferably, client 10 represents one or more lender servers, client 20represents one or more consumer devices, and client 30 represents one ormore credit bureau or other alternative data servers and/or devices.

It is contemplated herein that network 40 may be embodied inconventional and/or proprietary, wired and/or wireless, hardware and/orsoftware, integrated and/or modular means for sending and receivingdigital data, light, and/or electronic signals between processors, nodesor other addressable network sites coupled thereto. Moreover, it iscontemplated that server or client device functionality may be embodiedin one or more processing machines, devices, or combined components anda single processing machine, device, or combination of components mayperform functionality of multiple server and/or client processors.

In accordance with present invention, network 40 including loan brokerserver(s) 50 and client(s) 10, 20, 30 employs software and/or otherfunctionally equivalent firmware, hardware, or electronics forread/write operations with one or more digital data or digital memory orfunctionally equivalent network-accessible electronic storage to accessdata or store data about one or more clients 10, 20, 30 associated withpreviously stored, currently measured, or preferred network or nodeconfiguration, on-line network traffic, schedule events, or subscribedor qualified affiliation. Preferably, such software functionality isimplemented using embedded or real-time operating (RTOS) codeconvention, JAVA, C/C++, Windows/CE, or other equivalent digital signalprocessing instruction scheme, according to operational definitiondescribed herein.

Preferably, clients 10, 20, 30 are classified into or otherwiseassociated with sets, super-sets, sub-sets, groups, super-groups,sub-groups, or other hierarchical category according to pre-specified ordynamically defined criteria for qualification therein. Particular setor sets may be logically mapped, assigned contextually or otherwiserelated to one or more corresponding targeted on-line message orelectronic/optical network signals, as described herein. Additionally,network 40, including loan broker server(s) 50 and client(s) 10, 20, 30may employ software and/or other functionality for directing ortargeting on-line messages or electronic/optical signals to selected orclassified client set or group adaptively or dynamically according tomonitored or specified set characteristics or attributes. For example,one or more consumer devices with similar characteristics and requestingor with potential interest in certain types of products, incentives,information, or transactions may be grouped with one or more lenderservers that provide the requested products, incentives, information, ortransactions.

FIG. 2 depicts several of the key components of the lender server 10.Those of ordinary skill in the art will appreciate that the lenderserver 10 includes many more components than those shown in FIG. 2.However, it is not necessary that all of these generally conventionalcomponents be shown in order to disclose an enabling embodiment forpracticing the present invention. As shown in FIG. 1, the lender server10 is connected to the network 40 via a network interface 130. Those ofordinary skill in the art will appreciate that the network interface 130includes the necessary circuitry for connecting the lender server 10 tothe network 40, and is also constructed for use with the TCP/IPprotocol, other protocols such as IIOP, or other conventional digitalnetworking and data communications scheme.

The lender server 10 also includes a processing unit 110, a display 140,an output device 150, an operating system 155, and a mass memory 160 allinterconnected along with the network interface 130 via a bus 120. Theoutput device 150 could be any type of device capable of receivingoutput from the lender server 10, for example a printer, a smart cardreader, a plotter or a storage mechanism like a floppy, tape, DVD/CD-ROMdrive, or portable hard drive. The mass memory 160 generally comprises arandom access memory (“RAM”), a read-only memory (“ROM”), and one ormore permanent mass storage devices, such as a hard disk drive, tapedrive, optical drive, floppy disk drive, or combination thereof. Themass memory 160 stores the program code and data necessary forreceiving, processing, formatting, requesting or sending one or moreloan product names, related underwriting and pricing guidelines andcharacteristics, and related rates as well as supplying the results ofthat processing to other devices such as the loan broker server(s) viathe network 40 as shown in FIG. 1 in accordance with an embodiment ofthe present invention. More specifically, the memory 160 stores a loanproduct presenter process 170 to generate one or more loan productnames, related guidelines and characteristics, and related rates withina minimum level of compliance as shown and described in further detailwith reference to FIG. 6, the loan broker lender database 585.

Although an exemplary lender server 10 has been described that generallyconforms to a single conventional general purpose computing device,those of ordinary skill in the art will appreciate that a lender server10 may be a combination of computing devices or components, coordinatedto communicate with one or more loan broker servers 50 over a network40.

FIG. 3 depicts several of the key components of the customer device 20.Those of ordinary skill in the art will appreciate that the customerdevice 20 includes many more components than those shown in FIG. 3.However, it is not necessary that all of these generally conventionalcomponents be shown in order to disclose an enabling embodiment forpracticing the present invention. As shown in FIG. 1, the customerdevice 20 is connected to the network 40 via a network interface 230.Those of ordinary skill in the art will appreciate that the networkinterface 230 includes the necessary circuitry for connecting thecustomer device 20 to the network 40, and is also constructed for usewith the TCP/IP protocol, other protocols such as IIOP, or otherconventional digital networking and data communications scheme.Alternatively, a customer device 20 may be located with a customerservice representative who would submit information required forcreation of a consumer profile on the behalf of a potential customer whodoes not have direct access to the network 40 but is in direct contactwith the customer service representative via the globaltelecommunications network.

The customer device 20 also includes a processing unit 210, a display240, an output device 250, and a mass memory 260 all interconnectedalong with the network interface 230 via a bus 220. The output device250 could be any type of device capable of receiving output from thecustomer device 20, such as, but not limited to, a printer, a smart cardreader, a plotter or a storage mechanism like a floppy, tape orDVD/CD-ROM drive. The memory 260 generally comprises a RAM, a ROM, and apermanent storage device, such as a hard disk drive, tape drive, opticaldrive, floppy disk drive, or combination thereof. The memory 260 storesan operating system 270 and a Web browser 280. It will be appreciatedthat these software components may be loaded from a computer-readablemedium into memory 260 of the customer device 20 using a drive mechanism(not shown) associated with the computer-readable medium, such as afloppy, tape or DVD/CD-ROM drive or via the network interface 230.

Although an exemplary customer device 20 has been described thatgenerally conforms to a conventional general purpose computing device,those of ordinary skill in the art will appreciate that a customerdevice 20 may be any of a great number of devices capable ofcommunicating with the network 40, e.g., a cell phone including a smartphone, a wired or wireless personal digital assistant, workstation,laptop, an electronic wired or wireless handheld device, a tabletcomputer, etc.

FIG. 4 depicts several of the key components of the credit bureau oralternative data server or device 30. Those of ordinary skill in the artwill appreciate that the credit bureau or alternative data server ordevice 30 includes many more components than those shown in FIG. 4.However, it is not necessary that all of these generally conventionalcomponents be shown in order to disclose an enabling embodiment forpracticing the present invention. As shown in FIG. 1, the credit bureauor alternative data server or device 30 is connected to the network 40via a network interface 330. Those of ordinary skill in the art willappreciate that the network interface 330 includes the necessarycircuitry for connecting the credit bureau or alternative data server ordevice 30 to the network 40, and is also constructed for use with theTCP/IP protocol, other protocols such as IIOP, or other conventionaldigital networking and data communications scheme.

The credit bureau or alternative data server or device 30 may alsoinclude a processing unit 310, a display 340, an output device 350, anda mass memory 360 all interconnected along with the network interface330 via a bus 320. The output device 350 could be any type of devicecapable of receiving output from the credit bureau or alternative dataserver or device 30, such as, but not limited to, a printer, a smartcard reader, a plotter or a storage mechanism like a floppy, tape orDVD/CD-ROM drive. The mass memory 360 generally comprises a RAM, a ROM,and one or more permanent mass storage devices, such as a hard diskdrive, tape drive, optical drive, floppy disk drive, or combinationthereof. The mass memory 360 stores an operating system 370 and theprogram code and data necessary for receiving, processing, formatting,requesting and sending one or more credit bureau reports or alternativeinformation used to obtain credit rating or alternative data as well assupplying the results of that processing to other devices such as thelender servers 10, the customer devices 20, or the loan broker servers50 via the network 40 as shown in FIG. 1 in accordance with anembodiment of the present invention. More specifically, the mass memory360 stores a credit rating or alternative data service 380 to render andserve credit bureau reports or alternative data, for example incomeverification or employment verification or property title information orelectronic disclosures or electronic signatures, used to obtain creditrating or alternative information in response to a request from devicessuch as the loan broker server 50, as well as supplying the results ofthat processing to other devices such as the lender servers 10 and/orthe customer devices 20 via the network 40 in accordance with anembodiment of the present invention. Alternatively, the loan brokerserver 50 may communicate with alternative data server(s) or device(s)30 belonging to other institutions that deal with conforming loans,meaning the loans meet the criteria for maximum loan amounts and otherstandards set forth by Fannie Mae or Freddie Mac for example.

Although an exemplary credit bureau or alternative data server or device30 has been described that generally conforms to a single conventionalgeneral purpose computing device, those of ordinary skill in the artwill appreciate that a credit bureau or alternative data server ordevice 30 may be a combination of computing devices or components,coordinated to communicate with the loan broker server 50 or otherdevices over a network 40.

FIG. 5 depicts several of the key components of the loan broker server50. Those of ordinary skill in the art will appreciate that the loanbroker server 50 includes many more components than those shown in FIG.5. However, it is not necessary that all of these generally conventionalcomponents be shown in order to disclose an enabling embodiment forpracticing the present invention. As shown in FIG. 1, the loan brokerserver 50 is connected to the network 40 via a network interface 530.Those of ordinary skill in the art will appreciate that the networkinterface 530 includes the necessary circuitry for connecting the loanbroker server 50 to the network 40, and is also constructed for use withthe TCP/IP protocol or other protocols, such as the IIOP, or otherconventional digital networking and data communications scheme.

The loan broker server 50 also includes a processing unit 510, a display540, an output device 550, and a mass memory 560 all interconnectedalong with the network interface 530 via a bus 520. The output device550 could be any type of device capable of receiving output from theloan broker server 50, such as, but not limited to, a printer, a smartcard reader, a plotter or a storage mechanism like a floppy, tape orDVD/CD-ROM drive. The mass memory 560 generally comprises a RAM, a ROM,and one or more permanent mass storage devices, such as a hard diskdrive, tape drive, optical drive, floppy disk drive, or combinationthereof. The mass memory 560 stores an operating system 570 and theprogram code and data necessary for receiving, processing, formatting,requesting, and sending one or more loan product names, relatedunderwriting and pricing guidelines and characteristics, and relatedrates, as well as, supplying the results of that processing to otherdevices such as the customer device 20 in accordance with an embodimentof the present invention. The mass memory 560 includes a searchable loanbroker lender database 585 of the lender product names, underwriting andpricing guidelines and rates received, processed, and formatted from aplurality of lender servers 10. Additionally, the memory 560 stores aweb service 580 for providing web connectivity to the network 40 fordevices and servers with web browsers, such as the customer device(s) 20having web browser 280. The mass memory 560 also stores a data processor590 for creation and storage of one or more of a consumer profile 502 oradditional information required to initiate a transaction for one ormore of the loan products. The data processor 590 also contains thematching and optimization program logic which is utilized for thematching of a consumer's qualifications and needs as defined by theconsumer profile 502 to the best available loan products, and ranking ofthe available loan products and associated rate pricing as describedwith the flow chart of FIG. 9.

It will be appreciated that the aforementioned software components maybe loaded from a computer-readable medium into mass memory 560 of theloan broker server 50 using a drive mechanism (not shown) associatedwith the computer-readable medium, such as floppy, tape or DVD/CD-ROMdrive or via the network interface 530.

Although an exemplary loan broker server 50 has been described thatgenerally conforms to a conventional general purpose computing device,those of ordinary skill in the art will appreciate that a loan brokerserver 50 may be any of a great number of devices capable ofcommunicating via the network 40.

FIG. 6 shows a representation of fields within the loan broker lenderdatabase including the minimum compliance level of data in accordancewith an embodiment of the present invention. The actual database is anumerical matrix generated by receiving and storing data from aplurality of lending institutions. Each institution has specificunderwriting and pricing guidelines for the loan products that theyoffer comprising loan characteristics, qualifying ratios and limits,base rate pricing, yield spread rate pricing, and rate add-ons.Different lenders may require different information than one another andbase their individual loan qualification and pricing decisions ondifferent criteria. This invention may receive, modify, and store aminimum amount of information from each lending institution, the“minimum compliance level of data”, for use as described further in FIG.8 and FIG. 9. The fields included in the minimum compliance level ofdata are highlighted in bold in FIG. 6 and comprise credit score, loanamount, cash-out amount, loan-to-value ratio (LTV), combinedloan-to-value ratio (CLTV), front DTI, back DTI, PITI reserverequirements, tradeline requirements, payment history, bankruptcyhistory, foreclosure history/information, notice of defaulthistory/information, interest only versus fully amortizing, productterms, use of proceeds, lien position, property type, occupancy type,property location, documentation type, and employment type. Thisbaseline criteria is uniformly collected from each individual lender andis then modified as necessary, organized, and stored in conjunction withlike criteria from all other lending institutions.

Additional data may be received, modified, and stored in the loan brokerlender database for use in alternative embodiments of the presentinvention, for example disposable income requirements, reserverequirements, seasoning, acreage, square footage, properties owned, ratebuy-down “points”, yield spread (also known as service release premium,gain on sale, or rebate), prepayment penalty requirements, currently ownor rent, number of years in current job, number of years in currentindustry, number of years in current career, highest credit limit,number of years of credit on file, first time homebuyer requirements,escrowing taxes and insurance, prepayment penalties, lock terms,employment status (student, part time, etc), number of mortgagescurrently on property, source of down payment, has property been on themarket in last twelve months, other sources of income, party to alawsuit or not, is any of the down payment borrowed, current mortgage orloan insurance, citizenship status, residency status, co-borrowerrequirements, trailing spouse income, number of units owned, number ofloans to same bank, properties held in trust requirements, consumercredit history, judgments, liens, charge offs, second job, gift ofequity, gift funds, seller concessions, seller carry back, constructionloan, owner/builder loan, 1031 exchange, non traditionalcredit/tradelines (utility bills, phone bill, etc.), payment shock,(percent increase of current housing expense to proposed housingexpense), rental history, entity of borrower, age of borrower,immigration status, conservator and guardian involvement, non-borrowingspouse requirements, cash-out requirements, seller's length ofownership, multiple loans to same borrower, non-arm's length transactionrequirements, arm's length transactions, buy-down plans and terms,financing concessions, interested parties, escrow requirements,affordable seconds/subsidized financing requirements, trailing secondaryearner's income, income requirements, expense requirements, assetrequirements, documentation requirements, employment requirements, ageof credit report, delinquent accounts, collection accounts, creditreport requirements, or contingent liabilities.

The aggregation of such criteria from each of the plurality of lendinginstitution's underwriting and pricing guidelines forms the loan brokerserver's searchable and centralized lender database for use in matchingand optimizing loan products and associated rate pricing for a consumer.

FIG. 7 shows an overview flow diagram illustrating information obtainedand logic implemented using the devices of FIG. 1 to create a customconsumer profile in accordance with an embodiment of the presentinvention.

Utilizing some components of the loan broker computing apparatus of FIG.1, a consumer is able to use a customer device 20 to interact with theloan broker server 50 for the purpose of providing loan and propertyinformation, income information, and/or credit information used in thecreation of a consumer profile to be further used for searching acentralized database of a plurality of lending institutions'underwriting and pricing guidelines on behalf of that consumer. Creditinformation or alternative data may also be obtained automatically viacredit bureau or alternative data server(s) or device(s) 30 inalternative embodiments of the current invention.

Loan and property information comprises use of proceeds, property value,loan amount, cash-out amount, property location, property type,occupancy type, loan terms (for example fixed versus adjustable), lengthof loan, interest only loan or otherwise, seasoning on property (lengthof property ownership for refinancing), total number of propertiesowned, acreage, or square footage. Income information comprises type ofincome documentation, income, expenses, and value of liquid assets,property taxes, insurance cost, or employment information. Creditinformation comprises credit score(s) (FICO or otherwise), creditself-ranking, tradelines, payment history, bankruptcy history, consumercredit counseling history, or foreclosure or notice of default history.Additional information which may be obtained either directly from theconsumer or through communication between a loan broker server 50 andcredit bureau or alternative data server(s) or device(s) 30, for examplelien position, prepayment penalties, rate buy-down “points”, yieldspread, number of units owned, type of employment (self versussalaried), or notice of default may be used amongst others inalternative embodiments of the current invention.

This information is communicated to the loan broker server over thenetwork 40 using the network interface 230 and/or 330. Calculationswhich may then be performed by the loan broker server data processor 590comprise loan-to-value ratio (LTV), combined loan-to-value ratio (CLTV),front debt-to-income ratio (DTI), back DTI, disposable income, totaltradelines, principal, interest, property taxes, and insurance (PITI)reserves, number of late payments, time since bankruptcy, time sinceconsumer credit counseling, or time since foreclosure or notice ofdefault (NOD). Additional calculations necessary for matching theconsumer's qualifications and needs to the best available loan productswith associated rate pricing or to initiate or complete a transactionmay also be included in alternative embodiments. FIG. 10 shows arepresentative example of a consumer output that includes components ofthe custom consumer profile in accordance with an embodiment of thepresent invention.

The custom consumer profile may be stored in the loan broker server'smemory 560 for use further described below with reference to FIG. 9. Thecustom consumer profile may also be viewed by an output device 250 andconfirmed as correct or modified by the consumer.

FIG. 8 shows an overview flow diagram illustrating information obtainedand logic implemented using the devices of FIG. 1 to create a customloan broker lender database in accordance with an embodiment of thepresent invention.

Utilizing some components of the loan broker computing apparatus of FIG.1, a loan broker server 50 is able to interact with the lender server(s)10 over the network 40 for the purpose of creating, organizing, andupdating a centralized and searchable loan broker lender database 585 ofa plurality of lending institutions' underwriting and pricing guidelinesfor loan products. The loan broker lender database includes guidelines585-10 comprising qualifying limits 585-12 and characteristics 585-11,base rate pricing 585-20, yield spread pricing 585-30, and rate add-ons585-40 comprising base rate add-ons 585-41 and yield spread add-ons585-42 further comprising term add-ons 585-411 and stand alone add-ons585-43. The loan broker lender database 585 is comprised partly of aminimum compliance level of data obtained by the loan broker server(s)50 from each lender regarding that lender's loan products.

Every loan product has qualifying limits 585-12 that determine if aconsumer profile 502 stored in loan broker memory 560 qualifies for aparticular loan product. The qualifying limits and/or ratios comprisedata contained within the minimum compliance level of data except foremployment type. This includes but by definition is not limited tocredit score (FICO or other alternative scoring), loan amount, cash outamount, LTV (loan-to-value), max CLTV (combined loan-to-value), “front”DTI (debt-to-income), and “back” DTI. Qualifying limits may also includeother data, for example employment type, seasoning, square footage,acreage, number of properties owned, time of credit on file, chargeoffs,delinquent accounts, judgments, collections, or highest credit limit, aswell as others in accordance with alternative embodiments of the presentinvention and represented by numerical values. These qualifying limits585-12 are stored as a numerical matrix of qualifying factors anddetermine if a consumer and corresponding consumer profile qualifies forany of all existing loan products in the loan broker lender database.For example, a person may need a minimum FICO credit score of 500 toqualify for any of a particular lending institution's loan products.However, that same consumer may need a minimum FICO credit score of 620to qualify for a loan greater than $500,000 with that same lender. Theselimits act as “min” and “max” functions, and a consumer profile will notqualify for a particular product if it falls above or below those limitsin any category. The qualification process is a binary (“yes” or “no”)outcome.

The characteristics 585-11 are descriptors for a lending institution'sloan products and define the loan products that a lender offers inaccordance with an embodiment of the present invention. Thesecharacteristics comprise data contained within the minimum compliancelevel of data except for employment type. This includes but bydefinition is not limited to lien position, use of proceeds, propertytype, occupancy type, property location, terms, or documentation type.Characteristics may also include other data, for example lender name,product line name, first time homebuyer requirements, escrowrequirements, employment type, residency status, citizenship status,other cash out requirements, 1031 exchange requirements, down paymentrequirements and parameters, construction loan requirements, subsidizedfinancing requirements, or requirements for “arm's length” and“non-arm's length” transactions as well as others in accordance withalternative embodiments of the present invention. Each characteristicmay have options within it. For example, under “use of proceeds,” theoption may exist to use the loan for purchasing a home, refinancing ahome, or refinancing a home and taking cash out. Similarly under“terms,” there may be options for a 30 year fully amortizing fixedmortgage, a 3 year interest only adjustable rate mortgage (ARM), etc. Aloan product type is defined by the aggregate options within eachcharacteristic. The numerical matrix of the limits corresponds to thesecharacteristics and sub-categories, and the numerical matrix can beadditionally assigned to multiple sub-categories under eachcharacteristic.

In the present invention, these qualifying limits 585-12 andcharacteristics 585-11 are entered into a standard format into the loanbroker lender database 585 such that a plurality of numerical matricesmay be created within a lending institution's specific product line(s).A consumer profile 502 would be run against the sub-categories undereach characteristic to match the profile with the lenders' products tosee which lending institution(s) offer the product sought by theconsumer. The programming logic matches the appropriate numerical matrixin the loan broker lender database 585 to the loan product requested bythe consumer to see if the consumer's profile qualifies (“yes” or “no”)for that particular product.

In addition to qualifying limits and characteristics, every loan productalso has associated interest rate pricing, and the minimum compliancelevel of data includes two methods utilized for determining loan productpricing: base rate pricing 585-20 and yield spread rate pricing 585-30each coupled with the applicable rate add-ons 585-40.

Base rate pricing 585-20 is accomplished by creating within the lenderdatabase 585 a pricing matrix with rates determined by all factors thatcomprise the minimum compliance level of data except for tradelines,property type, occupancy type, front DTI, back DTI, PITI reserves, andemployment type. Determining factors of base rate pricing may alsoinclude, for example, tradelines, property type, occupancy type, frontDTI, back DTI, PITI reserves, and employment type, yield spread, ratebuy-down (“points”), rate lock terms, pre-payment penalty requirementsand terms, escrow requirements, seller concessions, seller carry-backs,as well as others in accordance with alternative embodiments of thepresent invention. Each individual lending institution may utilize andpresent this specific loan product information differently, and anembodiment of the present invention creates and updates a standardized,centralized and searchable loan broker lender database 585 containing inpart this information.

Yield spread rate pricing 585-30 determines pricing adjustments (alsoknown as Loan Level Pricing Adjustments or “LLPA”) corresponding to theparticular products in the pricing matrix and is accomplished bycreating within the loan broker lender database 585 a matrix of startingrates that correspond to a set of yield spreads (also known as servicerelease premiums, gains on sale, or rebates) and rate buy-downs that areassigned to a particular loan type (for example a 30 year fixedmortgage, a 3 year adjustable rate mortgage ARM, etc.) under a lender'sproduct line as determined by a lending institution. A higher yieldspread corresponds to a higher loan product interest rate, and a higherrate buy-down corresponds to a lower loan product interest rate. A yieldspread is a percentage paid to a lender as incentive for providing aconsumer a higher rate loan. For example, a lender may be able toprovide a consumer with a 6.0% loan and earn a 0.5% yield spread orservice release premium wherein the lender would be paid 0.5% of theloan. If the lender instead provided a consumer loan with a 5.75%interest rate, the lender might earn zero yield spread or servicerelease premium. A rate buy-down works the opposite way. A consumer maybe able to obtain a loan product with a rate of say 5.0% if 1% of theloan (a “point”) is paid in advance. Conversely, if no points are paid,the loan product interest rate may be higher, say 5.5%.

Yield spread rate pricing 585-30 is accomplished by creating within thelender database 585 a pricing matrix with rates determined by allfactors that comprise the minimum compliance level of data except fortradelines and PITI reserves. Determining factors of yield spread ratepricing may also include, for example, tradelines, PITI reserves, yieldspread, rate buy-down (“points”), number of properties owned, number ofunits owned, escrow requirements, as well as others in accordance withalternative embodiments of the present invention. These characteristicscreate pricing adjustments that impact the Yield Spread and RateBuy-Down assigned to a particular rate, and consequently impact theinterest rate presented to the consumer. Each lender's product line isassigned a particular type of pricing, base rate or yield spread rate,and the information and rates are entered for each respective lender.Each individual lending institution may utilize and present thisspecific loan product information differently, and an embodiment of thepresent invention creates and updates a standardized, centralized andsearchable loan broker lender database 585 containing in part thisinformation.

Once a consumer profile 502 is given a “yes” or “no” for qualificationof one or more of a lending institution's loan products, the profile ismatched against the rate pricing for a particular lender. Theprogramming logic matches the appropriate numerical matrix in the loanbroker lender database 585 to determine which rate is applied in boththe base rate and yield spread rate pricing scenarios for eachparticular loan product.

Rate add-ons 585-40 increase or decrease the rate pricing of a loanproduct based on the minimum compliance level of data except fortradelines and PITI reserves. Rate add-ons may also be determined byadditional criteria, including but not limited to tradelines, PITIreserves, yield spread, rate buy-down, seasoning (length of propertyownership), or escrow requirements for example among others as detailedin the consumer profile 502. For example, a consumer's profile mayqualify for a loan product with a base rate interest rate of 5%, but thefact that the consumer profile is using a property as a second homerather than the primary residence may result in a base rate add-on585-41 increase of 0.25%, for a total and final loan product parinterest rate of 5.25%.

Rate add-ons also comprise term add-ons 585-411. Term add-ons only applyto loan products that have base rate pricing 585-20 wherein a loanproduct rate will be determined or calculated based on the attributesand characteristics of another loan product, but with a specifiedincrease in rate. For example in accordance with an embodiment of thepresent invention, if a consumer profile requests a 3 year ARM, then theprogramming logic may determine or calculate a loan product interestrate for a specific 3 year ARM based off the rate matrix of a 2 yearARM, but with a term add-on 585-411 rate increase of 0.15%.

Rate add-ons also comprise stand alone add-ons 585-43. Stand-aloneadd-ons represent an increase or a decrease in the interest rate of aloan product or products within a lending institution's product line.Qualitative or quantitative qualifiers can trigger a stand-alone add-oneither in isolation or as a combination of both quantitative andqualitative qualifiers. Qualitative qualifiers 585-431 may includecertain components or combinations of components of the consumer profile502 including but not limited to lien position, use of proceeds,property type, or employment type. In the present invention, aqualitative qualifier works as a binary trigger. For example, if aproperty type equals a low rise condo, then there is a stand-aloneadd-on 585-43 rate increase of 0.25%. Quantitative qualifiers 585-432may include certain components of the consumer profile 502 including butnot limited to loan amount, front DTI, back DTI, or credit score (FICOor otherwise). A quantitative qualifier can work as a binary trigger ora less than/greater than trigger. For example, if the loan to value(LTV) is greater than or equal to 95%, then there is a stand-aloneadd-on 585-43 rate increase of 0.10%. In an alternative embodiment,programming logic may enable consumers to pay “points” (finance chargespaid by the consumer at the beginning of a loan whereas one point is 1%of the loan amount) either via a lump sum payment or as a percentage ofthe loan to secure a lower determined or calculated rate. This consumeroption and method of payment may then become an additional element ofthe consumer profile previously described.

In accordance with an embodiment of the present invention if a consumerprofile 502 qualifies for a lending institution's loan product(s), aninitial interest rate is determined for that loan product. Programminglogic as further described below and in accordance with FIG. 9 thenmatches the consumer profile with the appropriate rate add-ons 585-20,585-30, 585-40. The available loan products may then be matched andpresented with associated rate pricing to the consumer.

To better illustrate the matching of the consumer's qualifications andneeds to the best available loan products with associated rate pricing,FIG. 9 is a diagram illustrating one embodiment of actions taken by theloan broker server shown in FIG. 5 to present the consumer outputcomprising the ranking of loan products, rates, Annual Percentage Rate(APR), and monthly payments in response to a loan query in accordancewith an embodiment of the present invention. While home mortgages areused below to describe an illustrative loan product for which rates arepresented using guidelines and rate matching according to an embodimentof the present invention, those of ordinary skill in the art willappreciate that the present invention applies equally well to othertypes of loan products such as, but not limited to, auto, boat, secondmortgage, home equity loan, small business loan, commercial mortgage,student loan, personal loan, credit card, or other instances wherequalifications and rates are matched such as for insurance, a bankaccount, stock brokerage account, or retirement account. Other types ofloan products may exist without departing from the spirit of theinvention. Furthermore, certain steps in the program flow describedbelow must naturally precede others for the present invention tofunction as described. However, the present invention is not limited tothe order of the steps described if such order or sequence does notalter the functionality of the present invention. That is, it isrecognized that some steps may be performed before or after other stepsor in parallel with other steps without departing from the scope andspirit of the present invention.

The data processor 590 examines the consumer profile 502 and proceeds toselect all available loans based on the comparison of the consumerprofile to at least a portion of the minimum compliance level of databut often to the other qualification components of the loan brokerlender database 585. While the programming logic may determine that asingular loan product best meets the consumer's needs as detailed in theconsumer profile, a useful and innovative component of the presentinvention allows the data processor to combine a plurality of availableloan products to create and offer a combination of loans that may bestmeet the consumer's needs by providing a combined loan with the overalllowest monthly payments or lowest blended par rate. This best availableloan product may be a combination of loan products that are offered bythe same or a plurality of lending institutions. A “combo-loan” productwith an 80/20% ratio of two loans is described below; however, examplesexist because of this invention wherein the consumer may otherwiseobtain optimal loan product pricing with combinations of loans combinedin for example a 75/25% ratio, 90/10% ratio, or even for example a40/15/5% ratio of three individual loan products combined to satisfy aconsumer's need for a 60% LTV loan.

In the present example with an assumed LTV greater than 80%, the dataprocessor creates one or more additional temporary “dummy” consumerprofiles that allow for qualification of multiple loan products for thecreation of a combined best available loan product solution. Forexample, the desired loan amount could be divided into a first mortgageequal to exactly 80% of LTV and a second mortgage with the remainingLTV. If the desired LTV is 80% or less, the program logic could proceedwith only the first mortgage equal to that LTV as originally entered, orit could determine that a combination of mortgages could still providethe best solution for matching the consumer's qualifications and needsto the best available loan products with associated rate pricing.

The data processor 590 accomplishes this by next searching the loanbroker lender database 585 to obtain and match all rates 585-20, 585-30and rate add-ons 585-40 for the consumer profile 502 and calculatingmonthly payments based on the requested loan amount for each applicableloan product. The program logic does not calculate monthly payments forloan products that do not match the consumer profile regarding thefollowing fields: use of proceeds, property type, occupancy type,property location, and loan terms. The calculation of monthly paymentsdoes not include yield spread pricing adjustments or rate add-ons basedon the fields that are dependent on monthly payment amounts, for examplefront DTI, back DTI, PITI reserves, and disposable income.

Alternative embodiments exist for which the programming logic executesalternative steps in differing order; however, in the present examplethe data processor 590 next optimizes loan product pricing bycalculating monthly payments for all loan products that satisfy therequirements of the consumer profile (step f). If “combo” loans are asubset of all loan products available, then monthly payments arecalculated for traditional loan products followed by calculations forthe available combo loans (step g and gg).

For each available loan product, the data processor 590 now (step h)calculates the criteria in the consumer profile 502 that are dependenton the value of the monthly payment, namely: front DTI, back DTI, PITIreserves, and disposable income. Based on these calculations, rateadd-ons 585-40 are determined accordingly (step i). Monthly payments arerecalculated (step j) and steps b or step c through step j are repeatedby the data processor 590 in iterative fashion to conclusion of loanproduct pricing optimization.

The loan broker server(s) also have the ability to communicate withcredit bureau or alternative data servers or devices, for example, otherinstitutions that deal with conforming loans—that is, loans that meetthe criteria for maximum loan amounts and other standards set forth byFannie Mae and Freddie Mac. In alternative embodiments, consumers mayaccess the automated underwriting systems of such institutions (afterstep b of FIG. 9) or obtain access to the updated and stored informationvia the loan broker lender database. For example, the data processor 590may compare a consumer profile to the qualification standards of DesktopUnderwriter or Loan Prospector, the automated underwriting systems ofFannie Mae and Freddie Mac, respectively, do determine if the consumerqualifies for a conforming loan product. If so, the data processor mayalso obtain typically lower associated conforming loan rate pricing.

The consumer profile 502 is processed through the qualification enginefor comparison against the guidelines 585-05 of the loan broker lenderdatabase 585 by the data processor 590. All fields are comparedincluding front DTI, back DTI, PITI reserves, and disposable incomecalculated based on optimized pricing and accounting for all rateadd-ons as discussed above.

The data processor 590 has the data to rank all available loan productsaccording to interest rate, monthly payment, and Annual Percentage Rate(APR). The consumer output will rank both single mortgage options and/orcombination options to illustrate the best available loan products withassociated rate pricing (step k).

A representative example of this final consumer output is shown in FIG.10 in accordance with an embodiment of the present invention. In thisparticular example, FIG. 10A illustrates representative results for 3different types of loan products that the consumer desires and asdesignated in the consumer profile, namely a 3 year fully amortizingARM, a 5 year interest only ARM, and a 30 year fully amortizing fixedmortgage.

FIG. 10B shows a portion of the entire consumer profile (“Your ProfileAssumptions”), and in this example the consumer's desired loan-to-value(LTV) ratio is shown to be 100%. Therefore the qualification engine andprogramming logic matches this consumer need along with all otherqualifications and needs to a ranking of the best available loanproducts with associated rate pricing. In this example, the searchdetermines the best available loan products to be a single mortgage at100% LTV as well as a combination of mortgages for the 3 year fullyamortizing ARM. In the “multiple mortgages” (also know as “combo”mortgage) scenarios, the consumer may be able to obtain the bestavailable loan product and associated rate pricing by assuming two loansinstead of one. In some cases the multiple mortgages may be providedfrom a single lender while in others, the consumer may obtain the bestavailable loan product by receiving one mortgage from one lender and thesecond or additional mortgages from a different lender or lenders.

In this scenario, the consumer is unable to obtain a better loan productwith a combination of loans from the “5 year ARM, Interest Only” (FIG.10A) and “30 year fixed, Fully Amortizing” (FIG. 10B) loan products.This fact is evident because no minimum initial monthly payment orAnnual Percentage Rate (APRT is lower than that which is available for asingular or combination of “3 year ARM, Fully Amortizing” (FIG. 10A)loan products.

FIG. 10C shows an example of a typical legal disclaimer, and FIG. 10Dshows a representative example of a Good Faith Estimate of the closingcosts and fees involved in obtaining a loan. The title insurance cost orother closing costs and fees may be automatically determined orcalculated utilizing pre-determined formulae, data stored in the loanbroker lender database 585, or through communication with lender servers10 over the network 40, and these costs are listed as a portion of theconsumer output.

This invention allows individual consumers to conduct a customizedsearch of lenders and their loan products for the best mortgageincluding lowest rate, monthly payment, Annual Percentage Rate (APR),and/or closing costs and fees based on their needs and personal profile.Based on that information which consumers provide or which is obtainedthrough alternative methods, programming logic creates personalized loanprofiles based on consumers' financial and product information andstores those profiles in a database. Information in the form of lendingcriteria and guidelines is obtained from lenders and entered into astandardized, searchable database format. Programming logic has beeninvented which performs data interpretation, entry and maintenance ofeach lender's guidelines—including aggregation and presentation ofwholesale and retail loan product rates—since all lender information isnot individually presented in a single, standardized format. While ratematrices are often presented in similar formats, there has been nostandard way of presenting exceptions, yield spread pricing adjustments,rate add-ons, and product and credit standards.

This invention creates that standardization such that the consumerprofiles can then be matched against lenders' underwriting guidelines tooptimize product and pricing for the consumer. The novel search formatis also able to account for the numerous exceptions, pricingadjustments, and rate add-ons that can apply to lenders' underwritingguidelines. The invention is able to rank the available loan productsaccording to the desired criteria: rate, monthly payment, AnnualPercentage Rate, and associated fees and closing costs. Consumers maythen be informed as to exactly which lender or lenders will provide themwith the optimal loan product or combination of loan products based onthat customer profile.

The invention provides several advantages compared to current relatedtechnologies, although all advantages are not necessarily present inevery embodiment of the invention. The customized search engine providescomplete transparency into the loan process by presenting theinformation required to find the best available loan product at thelowest rate, monthly payment, Annual Percentage Rate (APR), andassociated fees and closing costs. This invention is not limited solelyto home mortgages, and in addition to obtaining the best available loanproduct, the consumer's direct search potentially enables avoidance ofthe traditional loan broker process and associated fees. Furthermore,because of the direct link established by the network between consumersand lenders, the loan broker server(s) allow lenders to find consumersjust as easily and efficiently as the consumers are now able to find thelenders and the associated loan products. Additional and alternativedata is also available from the credit bureau and alternative dataserver(s) or device(s) to provide more information faster orautomatically to improve or facilitate the search for as well asmatching of the best available loan products and consumers. With thisnewfound efficiency and transparency, transaction costs and overallcosts are also reduced. Once the best available loan products have beenselected, consumers may initiate and complete loan transactions for oneor more of the loan products with any of a plurality of lendinginstitutions (after step k of FIG. 9).

Foregoing described embodiments of the invention are provided asillustrations and descriptions. They are not intended to limit theinvention to the precise form described. Other variations andembodiments are possible in light of above teachings, and it is thusintended that the scope of invention not be limited by this DetailedDescription, but rather by the following claims.

What is claimed is:
 1. In a computer automated system comprising aprocessing unit and a memory element having instructions encodedthereon, a method for using Loan Level Pricing Adjustments correspondingto specific consumer input to determine or calculate the interest ratesof a plurality of loan products, the method comprising: creating,organizing, and updating a centralized and searchable lender database ordatabases comprised of a plurality of lending institutions' interestrate pricing for loan products, wherein the steps of creating,organizing and updating further comprise: aggregating interest ratematrices or grids and Loan Level Pricing Adjustment information for theloan products obtained from each lender, wherein said aggregation from aplurality of lending institution's interest rate matrices or grids andLoan Level Pricing Adjustments forms part of the searchable andcentralized database or databases for use in determining the interestrates for a consumer; determining or calculating interest rates for theloan products for said consumer based on input consumer criteria andcorresponding Loan Level Pricing Adjustments.
 2. The method of claim 1wherein a first subset database and all subsequent lender subsetdatabases are comprised of interest rate pricing that is uniformlycollected from each individual lender and is then modified as necessary,organized, and stored in conjunction with like criteria from all otherlending institutions.
 3. The method of claim 1 further comprisingreceiving and updating a first lender subset database and one or moresubsequent lender subset databases from said plurality of lendinginstitutions.
 4. The method of claim 1 further comprising the step ofallowing an additional lending institution to contribute that lendinginstitution's subset database of interest rates and Loan Level PricingAdjustments to a loan broker lender database.
 5. The method of claim 1wherein a first lender subset database and all subsequent lender subsetdatabases are organized into a numerical loan broker database matrixwith resulting data comprising the aggregated baseline criteria obtainedfrom each subset database required for determining loan pricing.
 6. Themethod of claim 1 wherein determining interest rates further comprises:performing one or more calculations using the consumer information toobtain credit related values; and creating a consumer profile comprisingconsumer information and the results of credit related valuecalculations.
 7. The method of claim 6, wherein consumer informationcomprises loan and property information, income information, or creditinformation.
 8. The method of claim 7 further comprises receiving creditinformation by a centralized web server via the Internet.
 9. The methodof claim 6, wherein the credit related value calculations performed byan additional computer or device comprise loan-to-value ratio (LTV),combined loan-to-value ratio (CLTV), front debt-to-income ratio (DTI),back debt-to-income (DTI), disposable income, principal, interest,property taxes, PITI (principal, interest, taxes, and insurance)reserves, number of late payments, time since bankruptcy, time sinceconsumer credit counseling, or time since foreclosure or notice ofdefault.
 10. The method of claim 6 further comprising the step ofencrypting consumer identification and the consumer information.
 11. Themethod of claim 1 further comprising defining by each lendinginstitution, their own baseline criteria, and wherein aggregatingcomprises aggregating the baseline criteria from each institution,wherein the baseline criteria is comprised in the minimum compliancelevel of data, which is defined by each of said lending institutions,such that each lending institution may have different criteria fordefining said minimum compliance level of data.
 12. The method of claim11 wherein said baseline criteria comprised in the minimum compliancelevel of data is required for determining loan eligibility and pricing,uniformly collected from each individual lender, and then modified,organized, and stored in conjunction with like criteria collected fromeach other lending institution.
 13. The method of claim 12 wherein thesaid baseline criteria further comprises at least one of credit score,loan amount, down payment, loan-to-value ratio (LTV), combinedloan-to-value ratio (CLTV), front debt-to-income (DTI), backdebt-to-income (DTI), payment history, bankruptcy history, foreclosurehistory/information, use of proceeds, property type, occupancy type,property location, and documentation type.
 14. The method of claim 13wherein the said baseline criteria further comprises at least one ofcash-out amount, PITI (principal, interest, taxes, and insurance)reserve requirements, tradelines, notice of default history/information,interest only versus fully amortizing, product terms, lien position, andemployment type.
 15. The method of claim 1 wherein the interest ratesare determined using input consumer credit score, scores, ranges ofscores, or credit self-ranking.
 16. The method of claim 1 wherein theinterest rates are determined using input type of property.
 17. Themethod of claim 1 wherein the interest rates are determined using inputoccupancy type.
 18. The method of claim 1 wherein the interest rates aredetermined using calculated loan-to-value ratio (LTV) or combinedloan-to-value ratio (CLTV).
 19. A computer automated system fordetermining or calculating the interest rates of a plurality ofavailable loan products using Loan Level Pricing Adjustmentscorresponding to specific consumer input criteria, the system comprisinga processing unit and a memory element having instructions encodedthereon, wherein the instructions cause the computer automated systemto: create, organize, and update a centralized and searchable lenderdatabase or databases comprised of a plurality of lending institutions'interest rate pricing for loan products; aggregate interest ratematrices or grids and Loan Level Pricing Adjustment information obtainedfrom each subset database, wherein said aggregation from a plurality oflending institutions' aggregate interest rate matrices or grids and LoanLevel Pricing Adjustments forms part of the searchable and centralizeddatabase or databases for use determining the interest rates for aconsumer; and determine or calculate interest rates for said loanproducts for a consumer based on input consumer criteria andcorresponding Loan Level Pricing Adjustments.
 20. The computer automatedsystem of claim 19 wherein first and subsequent lender databases arecomprised in at least one of an automatically and manually updatablecentralized web server.
 21. The computer automated system of claim 19wherein a first lender subset database and all subsequent lender subsetdatabases are organized into a numerical loan broker database matrixfunctioning as limits with resulting data comprising aggregated baselinecriteria obtained from each subset database required for determiningloan pricing.
 22. The computer automated system of claim 19 wherein theinstructions encoded thereon that cause the system to match and optimizeloan products or pricing for the consumer, further cause the system to:perform one or more calculations using the consumer information toobtain credit related values; and create a consumer profile comprisingconsumer information and the results of credit related valuecalculations.
 23. The computer automated system of claim 22, wherein theinstructions encoded thereon further cause the system to receive creditinformation from a centralized web server.
 24. The computer automatedsystem of claim 22 wherein the instructions encoded thereon furthercause the system to encrypt consumer identification and the consumerinformation.